Proteogenomic insights suggest druggable pathways in endometrial carcinoma
Authors: Yongchao Dou, Lizabeth Katsnelson, Marina A. Gritsenko, Yingwei Hu, Boris Reva, Runyu Hong, Yi-Ting Wang, Iga Kolodziejczak, Rita Jui-Hsien Lu, Chia-Feng Tsai, Wen Bu, Wenke Liu, Xiaofang Guo, Eunkyung An, Rebecca C. Arend, Jasmin Bavarva, Lijun Chen, Rosalie K. Chu, Andrzej Czekański, Teresa Davoli, Elizabeth G. Demicco, Deborah DeLair, Kelly Devereaux, Saravana M. Dhanasekaran, Peter Dottino, Bailee Dover, Thomas L. Fillmore, McKenzie Foxall, Catherine E. Hermann, Tara Hiltke, Galen Hostetter, Marcin Jędryka, Scott D. Jewell, Isabelle Johnson, Andrea G. Kahn, Amy T. Ku, Chandan Kumar-Sinha, Paweł Kurzawa, Alexander J. Lazar, Rossana Lazcano, Jonathan T. Lei, Yi Li, Yuxing Liao, Tung-Shing M. Lih, Tai-Tu Lin, John A. Martignetti, Ramya P. Masand, Rafał Matkowski, Wilson McKerrow, Mehdi Mesri, Matthew E. Monroe, Jamie Moon, Ronald J. Moore, Michael D. Nestor, Chelsea Newton, Tatiana Omelchenko, Gilbert S. Omenn, Samuel H. Payne, Vladislav A. Petyuk, Ana I. Robles, Henry Rodriguez, Kelly V. Ruggles, Dmitry Rykunov, Sara R. Savage, Athena A. Schepmoes, Tujin Shi, Zhiao Shi, Jimin Tan, Mason Taylor, Mathangi Thiagarajan, Joshua M. Wang, Karl K. Weitz, Bo Wen, C.M. Williams, Yige Wu, Matthew A. Wyczalkowski, Xinpei Yi, Xu Zhang, Rui Zhao, David Mutch, Arul M. Chinnaiyan, Richard D. Smith, Alexey I. Nesvizhskii, Pei Wang, Maciej Wiznerowicz, Li Ding, D.R. Mani, Hui Zhang, Matthew L. Anderson, Karin D. Rodland, Bing Zhang, Tao Liu, David Fenyö, Andrzej Antczak, Meenakshi Anurag, Thomas Bauer, Chet Birger, Michael J. Birrer, Melissa Borucki, Shuang Cai, Anna Calinawan, Steven A. Carr, Patricia Castro, Sandra Cerda, Daniel W. Chan, David Chesla, Marcin P. Cieslik, Sandra Cottingham, Rajiv Dhir, Marcin J. Domagalski, Brian J. Druker, Elizabeth Duffy, Nathan J. Edwards, Robert Edwards, Matthew J. Ellis, Jennifer Eschbacher, Mina Fam, Brenda Fevrier-Sullivan, Jesse Francis, John Freymann, Stacey Gabriel, Gad Getz, Michael A. Gillette, Andrew K. Godwin, Charles A. Goldthwaite, Pamela Grady, Jason Hafron, Pushpa Hariharan, Barbara Hindenach, Katherine A. Hoadley, Jasmine Huang, Michael M. Ittmann, Ashlie Johnson, Corbin D. Jones, Karen A. Ketchum, Justin Kirby, Toan Le, Avi Ma'ayan, Rashna Madan, Sailaja Mareedu, Peter B. McGarvey, Francesmary Modugno, Rebecca Montgomery, Kristen Nyce, Amanda G. Paulovich, Barbara L. Pruetz, Liqun Qi, Shannon Richey, Eric E. Schadt, Yvonne Shutack, Shilpi Singh, Michael Smith, Darlene Tansil, Ratna R. Thangudu, Matt Tobin, Ki Sung Um, Negin Vatanian, Alex Webster, George D. Wilson, Jason Wright, Kakhaber Zaalishvili, Zhen Zhang, Grace Zhao
Journal: Cancer Cell (2023)

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.